962 resultados para FLEXIBLE SIDE-CHAINS
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Référence bibliographique : Rol, 59361
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Référence bibliographique : Rol, 59363
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The view of the alumni greenhouse from the west side.
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South corner of front of Memorial Hall, Chapman College, Orange, California.
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Bioinformatics applies computers to problems in molecular biology. Previous research has not addressed edit metric decoders. Decoders for quaternary edit metric codes are finding use in bioinformatics problems with applications to DNA. By using side effect machines we hope to be able to provide efficient decoding algorithms for this open problem. Two ideas for decoding algorithms are presented and examined. Both decoders use Side Effect Machines(SEMs) which are generalizations of finite state automata. Single Classifier Machines(SCMs) use a single side effect machine to classify all words within a code. Locking Side Effect Machines(LSEMs) use multiple side effect machines to create a tree structure of subclassification. The goal is to examine these techniques and provide new decoders for existing codes. Presented are ideas for best practices for the creation of these two types of new edit metric decoders.
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The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.
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Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.
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Complex social-cognitive deficits are common in individuals diagnosed with high functioning autism and Asperger syndrome. Research on effective and evidence-based social interventions is needed for this population. This study focused specifically on the challenges these individuals face with respect to flexible thinking and related flexible behaviour in social situations. Madrigal and Winner's (2008) Superflex curriculum - targets social flexibility, however at the time of this study no published research had been conducted to determine the effectiveness of this approach. This study was a pilot study, which sought to examine the impact of the Superflex curriculum within a 10-week training program in teaching one individual with high functioning autism how to think and behave flexibly in social situations. Multiple measurement tools were utilized, and analyses within and across the measures revealed inconsistencies, especially with respect to generalization. Although preliminary, this study provided valuable information for subsequent research.
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Black and white photograph, mounted on board, 7 cm x 4 cm, of Julia in a side angle face pose. This photo was taken by Fred Pfaff of Peach Street, Erie, Pennsylvania.